Syllabus
Registration via LPIS
| Day | Date | Time | Room |
|---|---|---|---|
| Friday | 11/17/23 | 02:00 PM - 05:30 PM | D4.0.136 |
| Friday | 11/24/23 | 02:00 PM - 05:30 PM | D4.0.136 |
| Friday | 12/01/23 | 02:00 PM - 05:30 PM | D4.0.136 |
| Friday | 12/15/23 | 02:00 PM - 05:30 PM | D4.0.127 |
| Friday | 01/12/24 | 02:00 PM - 05:30 PM | D4.0.136 |
| Friday | 01/19/24 | 02:00 PM - 05:30 PM | D4.0.136 |
| Friday | 01/26/24 | 02:00 PM - 05:30 PM | D4.0.136 |
In this course we will cover topics that build on the courses Asset/Risk Management I and II. For each topic, we will bring models to the data. The topics covered are: portfolio construction; fund strategies; performance evaluation; risk premia of stocks, bonds, and other asset classes.
- Deepen state-of-the-art academic knowledge in the area of portfolio management.
- Gain deeper understanding of models by actually implementing them.
- Get familiar with financial time series.
- Learn to critically assess empirically results.
- Train capability for teamwork.
Full attendance is compulsory. This means that students should attend at least 80% of all lectures, at most one lecture can be missed.
Students have to prepare home assignments, which are usually based on an academic paper, and involve R programming and data work. Students work in small teams with changing team composition.
Grading is based on the following elements:
75% Quality of the submission (report, code, analysis)
25% individual presentations (number and quality of presentations)
There are 6 assignments. Grading is based on the 5 best submissions.
Grading scheme: [0-50): 5; [50-65): 4, [65-80): 3; [80-90): 2; [90-100]:1
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